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利用多时相干涉合成孔径雷达(InSAR)数据集探测和更新白鹤滩库区蓄水前后的滑坡清单

Detection and updation of landslide inventory before and during impoundment in the Baihetan reservoir area using multi-temporal InSAR datasets.

作者信息

Dun Jiawei, Feng Wenkai, Yi Xiaoyu, Ding Zhiwen, Zhuo Guanchen, Dai Keren, Wu Mingtang

机构信息

State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China.

College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, China.

出版信息

Sci Rep. 2025 Mar 22;15(1):9889. doi: 10.1038/s41598-025-94520-1.

Abstract

The Baihetan Hydropower Station, the second largest in the world, is currently impounded, posing significant challenges to reservoir slope stability and nearby community's safety. Thus, continuous monitoring as well as updation of landslide inventory is pressing requirements. InSAR technology, with its mm-scale precision and round-the-year usability, will be highly effective in this region. However, single-source SAR data are limited for long-term detection, and traditional atmospheric models in InSAR grapple with attenuating the external atmospheric disturbances caused by impoundment, affecting InSAR accuracy. Therefore, we used multi-source SAR data (ALOS PALSAR and Sentinel-1A/B), and used time-series InSAR with the GACOS atmospheric correction model to accurately detect and update landslide inventory before and during impoundment. The results show that a total of 52 landslides were detected, including 31 newly detected during impoundment. Among them, 22 landslides have toe slopes in direct contact with water. Comparing landslides before and during impoundment, deformations exhibit three behaviors: new deformation emergence, weakening of existing deformation, and continuous increase. These landslides mainly develop in landforms with an inclination angle of 30° to 40°, trending northeast and northwest, and an altitude of 800 to 1200 m. Most landslides reside in non-massive rock strata and are modulated by fault zones, and their frequency diminishes with increasing distance from the reservoir boundary. Moreover, the deformation time series results show that intense summer rainfall and rapid reservoir water level rise are key factors accelerating deformation in active landslides and reactivating unstable slopes. Thus, this research can be directly used for landslide prevention and mitigation in the Baihetan reservoir area, providing an important reference for detecting similar reservoir landslides in atmospherically influenced areas.

摘要

世界第二大水电站——白鹤滩水电站目前正在蓄水,这对水库边坡稳定性和附近社区安全构成了重大挑战。因此,持续监测以及更新滑坡清单成为紧迫需求。合成孔径雷达干涉测量(InSAR)技术具有毫米级精度且全年可用,在该地区将非常有效。然而,单源合成孔径雷达(SAR)数据用于长期检测存在局限性,InSAR中的传统大气模型难以减弱蓄水引起的外部大气干扰,影响InSAR精度。因此,我们使用了多源SAR数据(先进陆地观测卫星相控阵L波段合成孔径雷达和哨兵1A/1B),并采用时间序列InSAR结合全球对流层延迟与大气折射在线数据同化系统(GACOS)大气校正模型,在蓄水前和蓄水期间准确检测并更新滑坡清单。结果表明,共检测到52处滑坡,其中31处是在蓄水期间新发现的。其中,22处滑坡的坡脚与水直接接触。对比蓄水前和蓄水期间的滑坡情况,变形呈现出三种表现:新变形出现、现有变形减弱以及持续增加。这些滑坡主要发育在倾角为30°至40°、走向为东北和西北、海拔为800至1200米的地形中。大多数滑坡位于非块状岩层中,并受断裂带控制,其发生频率随着与水库边界距离的增加而降低。此外,变形时间序列结果表明,夏季强降雨和水库水位快速上升是加速活跃滑坡变形和使不稳定边坡复活的关键因素。因此,本研究成果可直接用于白鹤滩库区的滑坡防治,为在受大气影响地区检测类似水库滑坡提供重要参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a09/11929756/f322e895f7ec/41598_2025_94520_Fig1_HTML.jpg

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